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  1. MANUELA M. VELOSO . Head, J.P.Morgan Chase AI Research Herbert A. Simon University Professor Emerita 383 Madison Ave, New York, NY 10017 email: manuela.veloso at jpmchase dot com or mmv at cs dot cmu dot edu All PUBLICATIONS and AI in Finance PUBLICATIONS (When I was at CMU, to visit me, I would schedule

  2. Manuela Maria Veloso (born August 12, 1957) is the Head of J.P. Morgan AI Research & Herbert A. Simon University Professor Emeritus in the School of Computer Science at Carnegie Mellon University, where she was previously Head of the Machine Learning Department.

  3. Manuela M. Veloso (* 1957) ist eine portugiesisch-US-amerikanische Informatikerin, die sich mit Maschinenlernen, Künstlicher Intelligenz und Robotik befasst. Veloso studierte Elektrotechnik am Instituto Superior Técnico in Lissabon mit dem Master-Abschluss 1984 und Informatik an der Boston University mit dem Master-Abschluss 1986.

  4. Fast and inexpensive color image segmentation for interactive robots. J Bruce, T Balch, M Veloso. Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots …. , 2000. 876. 2000. Real-time randomized path planning for robot navigation. J Bruce, M Veloso. IEEE/RSJ international conference on intelligent robots and systems 3 ...

  5. Dr. Manuela Veloso is Head of J.P. Morgan Chase AI Research and Herbert A. Simon University Professor Emerita at Carnegie Mellon University, where she was previously Faculty in the Computer Science Department and Head of the Machine Learning Department. Her recent interests are in Artificial Intelligence (AI), Symbiotic Human-Robot Autonomy, ...

  6. Manuela M. Veloso is the Herbert A. Simon Professor of Computer Science at Carnegie Mellon University, researching artificial intelligence and robotics. She focuses on planning, control learning, and execution algorithms for single and multirobot systems, in particular in uncertain, dynamic, and adversarial environments.

  7. Head, AI Research/Prof CMU, JP Morgan. Manuela M. Veloso is the Head of J.P. Morgan AI Research, which pursues fundamental research in areas of core relevance to financial services, including data mining and cryptography, machine learning, explainability, and human-AI interaction.